NLP-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

Multi-task learning

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing
performance on one or all of the tasks.

DecaNLP

The Natural Language Decathlon (decaNLP) is a benchmark for studying general NLP
models that can perform a variety of complex, natural language tasks.
It evaluates performance on ten disparate natural language tasks.

GLUE

The General Language Understanding Evaluation benchmark (GLUE)
is a tool for evaluating and analyzing the performance of models across a diverse
range of existing natural language understanding tasks. Models are evaluated based on their
average accuracy across all tasks.